measureVariation | R Documentation |
Given a measure A
(object of class "msr"
)
these functions find the positive part, negative part and variation
of A
.
measurePositive(x) measureNegative(x) measureVariation(x) totalVariation(x)
x |
A measure (object of class |
The functions measurePositive
and measureNegative
return the positive and negative parts of the measure,
and measureVariation
returns the variation (sum of positive and
negative parts). The function totalVariation
returns the total
variation norm.
If μ is a signed measure, it can be represented as
μ = μ[+] - μ[-]
where μ[+] and μ[-]
are nonnegative measures called the positive and negative
parts of μ.
In a nutshell, the positive part of μ
consists of all positive contributions or increments,
and the negative part consists of all negative contributions
multiplied by -1
.
The variation |μ| is defined by
μ = μ[+] + μ[-]
and is also a nonnegative measure.
The total variation norm is the integral of the variation.
The result of measurePositive
, measureNegative
and measureVariation
is another measure (object of class "msr"
)
on the same spatial domain.
The result of totalVariation
is a non-negative number.
.
Halmos, P.R. (1950) Measure Theory. Van Nostrand.
msr
, with.msr
, split.msr
,
measureDiscrete
X <- rpoispp(function(x,y) { exp(3+3*x) }) fit <- ppm(X, ~x+y) rp <- residuals(fit, type="pearson") measurePositive(rp) measureNegative(rp) measureVariation(rp) # total variation norm totalVariation(rp)
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